code: def get_non_refinement_pipeline():
      node_encoding = PipelineNode("one_hot_encoding")
      node_scaling = PipelineNode("scaling", nodes_from=[node_encoding])
  
      node_lasso = PipelineNode("lasso", nodes_from=[node_scaling])
      node_dtreg = PipelineNode("dtreg", nodes_from=[node_scaling])
      node_dtreg.parameters = {"max_depth": 3}
  
      final_node = PipelineNode(
          "ridge", nodes_from=[node_lasso, node_dtreg]
      )
  
      pipeline = Pipeline(final_node)
      return pipeline
  
file_path: FEDOT/examples/advanced/decompose/regression_refinement_example.py
imports: import warnings
  import numpy
  import pandas
  from golem.core.tuning.simultaneous import SimultaneousTuner
  from sklearn.metrics import mean_absolute_error, mean_squared_error
  from sklearn.model_selection import train_test_split
  from fedot.core.data.data import InputData
  from fedot.core.pipelines.node import PipelineNode
  from fedot.core.pipelines.pipeline import Pipeline
  from fedot.core.pipelines.tuning.tuner_builder import TunerBuilder
  from fedot.core.repository.dataset_types import DataTypesEnum
  from fedot.core.repository.metrics_repository import RegressionMetricsEnum
  from fedot.core.repository.tasks import Task, TaskTypesEnum
  from fedot.core.utils import fedot_project_root
label_desc: Use image node_id 2 for calling a global function with example usage: get_non_refinement_pipeline() and returns: pipeline